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Qualitative Forecasting Methods and Techniques

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Managers use forecasts for budgeting purposes. A forecast aids in determining volume of production, inventory needs, labor hours required, cash requirements, and financing needs. A variety of forecasting methods are available. However, consideration has to be given to cost, preparation time, accuracy, and time period. The manager must understand clearly the assumptions on which a particular forecast method is based to obtain maximum benefit.

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This post provides overview of available forecasting methods, particularly the qualitative approach.

Management in both private and public organizations typically operates under conditions of uncertainty or risk. Probably the most important function of business is forecasting, which is a starting point for planning and budgeting. The objective of forecasting is to reduce risk in decision making.

In business, forecasts form the basis for planning capacity, production and inventory, manpower, sales and market share, finances and budgeting, research and development, and top management’s strategy. Sales forecasts are especially crucial aspects of many financial management activities, including budgets, profit planning, capital expenditure analysis, and acquisition and merger analysis.

Marketing managers – They use sales forecasts to determine optimal sales force allocations, set sales goals, and plan promotions and advertising. Market share, prices, and trends in new product development are also required.

Production planners – They need forecasts in order to: schedule production activities, order materials, establish inventory levels and plan shipments. Other areas that need forecasts include material requirements (purchasing and procurement), labor scheduling, equipment purchases, maintenance requirements, and plant capacity planning. As soon as the company makes sure that it has enough capacity, the production plan is developed. If the company does not have enough capacity, it will require planning and budgeting decisions for capital spending for capacity expansion. On this basis, the manager must estimate the future cash inflow and outflow. He or she must plan cash and borrowing needs for the company’s future operations. Forecasts of cash flows and the rates of expenses and revenues are needed to maintain corporate liquidity and operating efficiency. In planning for capital investments, predictions about future economic activity are required so that returns or cash inflows accruing from the investment may be estimated. Forecasts are needed for money and credit conditions and interest rates so that the cash needs of the firm may be met at the lowest possible cost. Forecasts also must be made for interest rates, to support the acquisition of new capital, the collection of accounts receivable to help in planning working capital needs, and capital equipment expenditure rates to help balance the flow of funds in the organization. Sound predictions of foreign exchange rates are increasingly important to managers of multinational companies. Long-term forecasts are needed for the planning of changes in the company’s capital structure. Decisions on issuing stock or debt to maintain the desired financial structure require forecasts of money and credit conditions.

The personnel department – It requires a number of forecasts in planning for human resources. Workers must be hired, trained, and provided with benefits that are competitive with those available in the firm’s labor market. Also, trends that affect such variables as labor turnover, retirement age, absenteeism, and tardiness need to be forecast for planning and decision making.

Managers of nonprofit institutions and public administrators – They also must make forecasts for budgeting purposes.

Hospital administrators – They forecast the healthcare needs of the community. In order to do this efficiently, a projection has to be made of: growth in absolute size of population, changes in the number of people in various age groupings, and varying medical needs these different age groups will have.

Universities – These forecast student enrollments, cost of operations, and, in many cases, the funds to be provided by tuition and by government appropriations.

The service sector – Today accounts for two-thirds of the U.S. gross domestic product, including banks, insurance companies, restaurants, and cruise ships, needs various projections for its operational and long-term strategic planning.

The bank – Banks have to forecast too. Demands of various loans and deposits Money and credit conditions so that it can determine the cost of money it lends.

Forecasting Methods

The company may choose from a wide range of forecasting techniques. There are basically two approaches to forecasting, qualitative and quantitative:

Approach#1. Qualitative

Using qualitative approach, a company forecasts based on judgment and opinion. Groupped under this approach are:

b. Associative (causal) forecasts – Grouped under the acsociative forecasts are the followings:

Simple regression

Multiple regression

Econometric modeling

Selection of Forecasting Method

The choice of a forecasting technique is influenced significantly by the stage of the product life cycle and sometimes by the firm or industry for which a decision is being made. In the beginning of the product life cycle, relatively small expenditures are made for research and market investigation.

During the first phase of product introduction, these expenditures start to increase. In the rapid growth stage, considerable amounts of money are involved in the decisions, so a high level of accuracy is desirable. After the product has entered the maturity stage, the decisions are more routine, involving marketing and manufacturing. These are important considerations when determining the appropriate sales forecast technique.

After evaluating the particular stages of the product and firm and industry life cycles, a further probe is necessary. Instead of selecting a forecasting technique by using whatever seems applicable, decision makers should determine what is appropriate.

Some of the techniques are quite simple and rather inexpensive to develop and use. Others are extremely complex, require significant amounts of time to develop, and may be quite expensive. Some are best suited for short-term projections, others for intermediate- or long-term forecasts.

What technique or techniques to select depends on six criteria:

What is the cost associated with developing the forecasting model, compared with potential gains resulting from its use?

How complicated are the relationships that are being forecasted?

Is it for short-run or long-run purposes?

How much accuracy is desired?

Is there a minimum tolerance level of errors?

How much data are available? Techniques vary in the amount of data they require.

The choice is one of benefit-cost trade-off. Quantitative models work superbly as long as little or no systematic change in the environment takes place. When patterns or relationships do change, by themselves, the objective models are of little use. It is here where the qualitative approach, based on human judgment, is indispensable. Because judgmental forecasting also bases forecasts on observation of existing trends, they too are subject to a number of shortcomings. The advantage, however, is that they can identify systematic change more quickly and interpret better the effect of such change on the future.

Next, let us have a look at the qualitative forecasting method on the next section [I will take several quantitative methods, along with their illustrations, next time].

Qualitative Forecasting Methods

The qualitative (or judgmental) approach can be useful in formulating short-term forecasts and can also supplement the projections based on the use of any of the quantitative methods.

Four of the better-known qualitative forecasting methods are executive opinions, the Delphi method, sales-force polling, and consumer surveys:

1. Executive Opinions

The subjective views of executives or experts from sales, production, finance, purchasing, and administration are averaged to generate a forecast about future sales. Usually this method is used in conjunction with some quantitative method, such as trend extrapolation. The management team modifies the resulting forecast, based on their expectations.

The advantage of this approach: The forecasting is done quickly and easily, without need of elaborate statistics. Also, the jury of executive opinions may be the only means of forecasting feasible in the absence of adequate data.

The disadvantage: This, however, is that of group-think. This is a set of problems inherent to those who meet as a group. Foremost among these are high cohesiveness, strong leadership, and insulation of the group. With high cohesiveness, the group becomes increasingly conforming through group pressure that helps stifle dissension and critical thought. Strong leadership fosters group pressure for unanimous opinion. Insulation of the group tends to separate the group from outside opinions, if given.

2. Delphi Method

This is a group technique in which a panel of experts is questioned individually about their perceptions of future events. The experts do not meet as a group, in order to reduce the possibility that consensus is reached because of dominant personality factors. Instead, the forecasts and accompanying arguments are summarized by an outside party and returned to the experts along with further questions. This continues until a consensus is reached.

Advantages: This type of method is useful and quite effective for long-range forecasting. The technique is done by questionnaire format and eliminates the disadvantages of group think. There is no committee or debate. The experts are not influenced by peer pressure to forecast a certain way, as the answer is not intended to be reached by consensus or unanimity.

Disadvantages: Low reliability is cited as the main disadvantage of the Delphi method, as well as lack of consensus from the returns.

3. Sales Force Polling

Some companies use as a forecast source salespeople who have continual contacts with customers. They believe that the salespeople who are closest to the ultimate customers may have significant insights regarding the state of the future market. Forecasts based on sales force polling may be averaged to develop a future forecast. Or they may be used to modify other quantitative and/or qualitative forecasts that have been generated internally in the company.

The advantages of this forecast are:

It is simple to use and understand.

It uses the specialized knowledge of those closest to the action.

It can place responsibility for attaining the forecast in the hands of those who most affect the actual results.

The information can be broken down easily by territory, product, customer, or salesperson.

The disadvantages include: salespeople’s being overly optimistic or pessimistic regarding their predictions and inaccuracies due to broader economic events that are largely beyond their control.

4. Consumer Surveys

Some companies conduct their own market surveys regarding specific consumer purchases. Surveys may consist of telephone contacts, personal interviews, or questionnaires as a means of obtaining data. Extensive statistical analysis usually is applied to survey results in order to test hypotheses regarding consumer behavior.

Common Features and Assumptions Inherent in Forecasting

As pointed out, forecasting techniques are quite different from each other. But four features and assumptions underlie the business of forecasting. They are:

Forecasting techniques generally assume that the same underlying causal relationship that existed in the past will continue to prevail in the future. In other words, most of our techniques are based on historical data.

Forecasts are rarely perfect. Therefore, for planning purposes, allowances should be made for inaccuracies. For example, the company should always maintain a safety stock in anticipation of a sudden depletion of inventory.

Forecast accuracy decreases as the time period covered by the forecast (i.e., the time horizon) increases. Generally speaking, a long-term forecast tends to be more inaccurate than a short-term forecast because of the greater uncertainty.

Forecasts for groups of items tend to be more accurate than forecasts for individual items, because forecasting errors among items in a group tend to cancel each other out. For example, industry forecasting is more accurate than individual firm forecasting.

About AuthorLie Dharma Putra

Putra is a CPA. His last position, in the corporate world, was a controller for a corporation in Costa Mesa, CA. After spending 15 years as a nine-to-five employee, he decided to serve more companies, families and even individuals, as a trusted business advisor. He blogs about accounting, finance and tax, during his spare time, and helps accounting students (around the globe) to understand the subject matter easier , faster. Follow him on twitter @LieDharmaPutra or add him to your circle at Google Plus Lie+

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